Well logging is an essential process in the oil industry to obtain information regarding a subsurface formation. The logging process is typically done in a drilled well, and is referred to as wireline logging process. The electromagnetic (EM) logging tool is one of the most widely used logging devices in the wireline logging process.
In the last few decades, the development of data interpretation methods in the oil industry is shifting from signal processing to inversion-based analysis. Signal-processing techniques are successful in enhancing data in terms of tail effect removal and resolution increasing. These techniques work well when the formation to be examined is mostly homogeneous and isotropic. However, when the formation profiles become complex, signal-processing methods fail to accurately describe the true formation. Especially in scenarios when high relative dip is involved in the logging process, measurements can include the signatures of multiple beds and second-order effects. In these cases, inversion schemes with a well-chosen parametric model may be employed. If the parametric model can describe the downhole background environment and the dip of the logging tool well, inversion methods can reconstruct radial profiling of the formation. With more and more deviated or horizontal wells being drilled, inversion techniques have become a major part of the research in the oil field industry.
For inversion methods, special attention has been paid to the computational efficiency of the forward modeling technique. Generally speaking, both forward and inverse problems are involved in an imaging algorithm. Among the available algorithms, iterative inversion techniques are the obvious choices for oil reservoir imaging problems due to their computational efficiency. However, in an iterative inversion method, the forward problem is solved in each of its iterations. As a result, the efficiency of the whole imaging process depends on the performance of the method used for the forward problem.
In an induction logging process, especially in a single well setup, canceling the direct coupling from transmitter to receivers is very important in terms of increasing the sensitivity of the tool. The original idea of bucking dates back to 1936 when an extra transmitting or receiver coil was used to counteract the effect of direct coupling. Since then, various bucking techniques were proposed to achieve better bucking effect. For instance, a symmetric structure was introduced that applied an extra bucking coil to balance the bucking effect. More complex circuit designs for bucking coils were also proposed to control both the amplitude and phase of the bucking signal. To further cancel out the bucking signal, a 4 coil system was proposed. Regardless of the method used, the one and only purpose of bucking is to cancel the direct coupling on the main receiver coil.
However, the introduction of bucking can cause problems in inversion based logging data interpretations. As mentioned, the algorithm for forward modeling needs to be efficient. Since the forward modeling of the induction logging is source dependent and the extra bucking coils can be considered extra sources in the system, the existence of bucking coils can significantly increase the computation complexity of a forward problem because each of the receiving locations are associated with a specific bucking coil. Therefore, in order to obtain an accurate estimation of the received field at receivers, forward calculations need to be done for each individual receiver coil. Depending on the number of receivers mounted on the logging tool, this extra calculation can significantly increase the computation complexity of the inverse technique.
In view of the foregoing, there is a desire for a logging tool which facilitates generation of an accurate subsurface formation profile for deep wells, with optimum computational complexity, and without compromising on accuracy of secondary field data on the receiver.